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The increasing of distributed energy and flexible load incentivize market participants to participate in a more active market. A coordinated peer to peer (P2P) trading model with an aggregated alliance and reserve purchasing is proposed in this paper. Under such a coordinated trading model, the market participants form an alliance, where the agents perform aggregated alliance and purchase reserve from a mobile energy storage supplier. To reduce the risk of deviation penalty in P2P trading, the agents seek to maximize the welfare of the entire alliance in the P2P process, while considering product differentiation and deviation risks. The proposed trading model design comprises: (i) a coordinated P2P market design with the aggregated alliance and reserve purchasing, (ii) a two-stage P2P market-clearing model to maximize trading utility while reducing the risk of deviation. To solve this two-stage multivariable coupling problem in a distributed way, we propose a primal–dual based ADMM method. Through the case study, compared with the traditional P2P trading model, the proposed market model can reduce the deviation penalty and improve the comprehensive welfare, while the convergence can be effectively guaranteed.

Multi-energy microgrid (MEMG) is a typical realization of multi-energy system. Its day-ahead dispatch is crucial for the economic operation of MEMG. However, previous research usually considered the efficiency of multi-energy coupling equipment in MEMG as a constant value neglecting the non-linear relationship of heterogeneous energy conversion. With this, day-ahead dispatch would result in inappropriate plans and further impair safe operation of MEMG. To deal with this challenge, this paper studies a novel day-ahead dispatch model for MEMG by considering variable operating conditions of multi-energy coupling equipment. Specifically, first, a novel day-ahead dispatch model of MEMG is proposed. The day-ahead dispatch model incorporates refined energy conversion constraints, and these constraints can capture variable operating conditions of multi-energy coupling equipment. Then, due to the non-linear terms with respect to variable operating conditions, a piecewise linearization method is utilized to transform the proposed model into a mixed-integer linear programming formulation. Finally, simulation results show that our approach can obtain a more reasonable day-ahead dispatch scheme with multiple advantages, such as improving the overall operating economy, avoiding multi-energy power curtailment, and enhancing the potential of demand response.

An experimental investigation concerning the convective heat transfer of n-decane maintained at supercritical operating pressures and flowing through a 2-mm-diameter and 200-mm-long pipe under conditions of varying rotational speeds, mass flow rates, inlet temperatures, and heat flux has been reported. The wall temperature was measured at four positions around the pipe periphery at five selected cross-sections along the pipe length. Maximum convective heat transfer was observed along the trailing edge of the centrifugal section while its corresponding minimum was observed along the leading edge. Heat transfers along the two sides of the channel were observed to be nearly identical. The average sectional convective heat-transfer coefficient demonstrated an increase with increase in rotational speed, and its value corresponding to 1500 rpm was observed to lie within the range of approximately 2–2.5 times its corresponding value under static conditions. The strong effect of the buoyancy force caused by the centrifugal force and flow deceleration due to pressure drop tended to limit the deterioration of local heat transfer. This study proposes an expression for a dimensionless criterion concerning the buoyancy force generated under rotating conditions along with a new local Nusselt number correlation apropos the heat transfer of n-decane flowing through a rotating centrifugal section under supercritical operating pressures.

Disorderly charging of large-scale electric vehicles (EVs) would result in the peak electricity consumption, damaging the safe and economic operation of power systems. As an important managing technique of distributed energy resources (DERs), virtual power plant (VPP) can effectively improve the charging strategies of EVs. With this, this paper proposes a bi-level optimal scheduling model of VPP with aggregated plug-in electric vehicles (PEVs) and a battery swapping station, and to optimize the charging/discharging of PEVs and batteries in battery swapping station. Based on the Stackelberg game, the leader is a VPP operator. It guides the charging/discharging behavior of PEVs using reasonable prices. As the followers, PEV owners adjust their charging/discharging strategies based on the leader’s price information. The Karush-Kuhn-Tucker (KKT) conditions are used to transform the bi-level model into a single-level formulation. Numerical results demonstrate that the proposed model can effectively improve overall economic benefits of the VPP, while respecting the interest of each PEV owners. Besides, charging/discharging of EVs are improved sustaining the safe operation of power systems.

Regenerative cooling is being used to meet the high cooling requirements of advanced hypersonic flight vehicles using the fuel at supercritical pressures as the coolant. The heat transfer and therm...

The experimental and numerical investigations of the heat transfer of supercritical pressure n-decane flowing through a pipe at various rotational speeds, mass flow rates, heat fluxes, and pressures, are presented. This pipe is 2 mm in diameter, 200 mm in length, with a radius of 0.328 m, and is parallel to the rotating axis. The wall temperature was measured at four positions around the periphery of the pipe at each of the five selected cross section along the pipe's length. Maximum convective heat transfer was observed at the outer edge of the horizontal section, while its corresponding minimum was observed at the inner edge. The heat transfers at the two sides of the channel were observed to be similar. The density and pressure differences between the outer and inner edges increased at increasing rotating speeds. However, the temperature difference between the outer and inner edges decreased with increased rotational speed mainly because of the increase of secondary flows in the section. The section's average convective heat transfer coefficient increased with an increase in the rotational speed, and its value at 1000 rpm was approximately twice than that at static conditions. The phenomenon of oscillation was observed near the exit of the horizontal section, and was caused by the flow and considerable property changes near the pseudo critical temperature. A computational fluid dynamics (CFD) model was developed using the real gas thermal properties and was coupled with the heat transferred owing to fuel flow. The predicted fuel and wall temperatures were in good agreement with the experimental data. A new local Nusselt number correlation of the heat transfer of n-decane in a rotating horizontal section was proposed.

With the rapid development of China's electricity market, the purchasing and selling strategies of electricity retailers (ER) have attracted great concern. Taking demand side response into account, this paper proposes a comprehensive profit optimization model, which takes bilateral risks in both purchasing and selling businesses of electricity market into consideration. In the proposed model, the scale spatial clustering method is used to generate multi-variant scenario with an adaptive gradient tracking, including the spot price, the output of renewable energy, demand-response (DR) behaviors and the random fluctuation of demand from users. Moreover, the external environment of demand response in power market is taken in consideration, which reflected in the interruptible load and transferable load profit model. Based on the probabilistic scenario, the day-ahead strategies of the ER are randomly optimized, considering the bilateral business of purchasing and selling profiles. Utilizing the simulation of case studies, the results show that the proposed model is suitable and effective to be used for determining the purchasing and selling strategy of the electricity-sales companies.

To meet the practical needs of rapid and non-destructive detection in fruit and vegetable processing, this paper designs a developed portable near-infrared spectrum quality-detection device. In this design, the digital micromirror device of the near-infrared micro-electromechanical system is used as the light splitting element, and the detection information is obtained by a single-point detector, to realize the miniaturization design of the spectrum detection system and significantly reduce the cost. Moreover, the quality inspection model is established based on the PLS method and the principal component analysis method. From the results of the prediction set, the model established by the logarithm of the original absorption spectrum (1/R) and the PLS method is applicable, with a high correlation coefficient (0.9537) and low corrected root mean square error (0.3776). This research can provide reference data for the design of low-cost, practical, and miniaturized near-infrared spectrum detection systems.

Research and/or Engineering Questions/Objective: The crashworthiness and lightweight of a vehicle were directly affected by the front structure of body frame, including the front-end impact beam, side rails, crash boxes and A-pillars. The key to lightweight is how to design a body frame that could reduce weight and meet safety requirements. The design optimization method based on finite element simulation could save cost and improve efficiency. In this research, this method is applied to the safety and lightweight design of the body frame, and a parametrical design optimization method is explored in consideration of safety and lightweight, offering technical support for automotive lightweight design. Methodology: Firstly, a parametrical modelling process was implemented on the substructure of a certain car according to the parametrical simulation. Secondly, a design optimization model was established with the parameters of body frame as the design variables, lightweight as the objective, and the front crashworthiness as the constraint. Thirdly, the design optimization model was solved and the optimal design parameters were obtained. Finally, the real vehicle was built up with optimal design parameters and experimental validation was carried out for safety and lightweight. Results: The fast modelling method about parametrical finite element model of body frame was constructed in the study, taking a real car of a Chinese domestic brand as the example. The optimization of finite element design method based on crashworthiness and lightweight of body frame was achieved and this method takes the safety and lightweight into account at the same time. It serves as an effective way to improve the efficiency of vehicle lightweight. Limitations of this study: Due to the complexity of vehicle structure, the parametrical design was merely implemented on some key sizes and parts which can affect structure strength obviously, however, the crash safety and lightweight requirement could be fulfilled from the final parametrical design. What does the paper offer that is new in the field including in comparison to other work by the authors? Through this parameterization process, which was based on the substructure, the rapid modifications of actual structures and automatic finite element model development became reality. Therefore, this technique was different to the parametrical designs and simulations of the traditional CAD/CAE method. Conclusions: The fast modelling method of finite element parametrical model and its optimization in respect of safety and lightweight is feasible. It can offer technical support for automotive lightweight.